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DeBERTa v3 (small) fine-tuned on SST2

This model is a fine-tuned version of microsoft/deberta-v3-small on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2134
  • Accuracy: 0.9404

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.176 1.0 4210 0.2134 0.9404
0.1254 2.0 8420 0.2362 0.9415
0.0957 3.0 12630 0.3187 0.9335
0.0673 4.0 16840 0.3039 0.9266
0.0457 5.0 21050 0.3521 0.9312

Framework versions

  • Transformers 4.13.0.dev0
  • Pytorch 1.10.0+cu111
  • Datasets 1.15.1
  • Tokenizers 0.10.3
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Dataset used to train mrm8488/deberta-v3-small-finetuned-sst2

Evaluation results